gamma_bootstrapper: Function to bootstrap the Cumulative Distribution Functions...

In TMTI: 'Too Many, Too Improbable' (TMTI) Test Procedures

Function to bootstrap the Cumulative Distribution Functions (CDFs) of the TMTI statistics.

Description

Function to bootstrap the Cumulative Distribution Functions (CDFs) of the TMTI statistics.

Usage

gamma_bootstrapper(m, n = Inf, B = 1000, mc.cores = 1L, tau = NULL, K = NULL)

Arguments

m	Number of tests.
n	Number (or Inf) indicating what kind of minimum to consider. Defaults to Inf, corresponding to the global minimum.
B	Number of bootstrap replicates. Rule of thumb is to use at least 10 * m.
mc.cores	Integer denoting the number of cores to use when using parallelization, Defaults to 1, corresponding to single-threaded computations.
tau	Numerical (in (0,1)); threshold to use in tTMTI. If set to NULL, then either TMTI (default) or rtTMTI is used.
K	Integer; Number of smallest p-values to use in rtTMTI. If se to NULL, then either TMTI (default) or tTMTI is used.

Value

An approximation of the function γ^m(x) under the assumption that all p-values are independent and exactly uniform.

Examples

## Get an approximation of gamma
gamma_function = gamma_bootstrapper(10)
## Evaluate it in a number, say .2
gamma_function(.2)

TMTI documentation built on Aug. 10, 2022, 5:06 p.m.